360-DQHM: A Phase-Topology-Based Memory Architecture Achieving O(1) Search Complexity at Billion-Entry Scale

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Authors: Shigeyuki Matsunaga
Cited by: 0

Abstract

We present 360-DQHM (360-Dimensional Dynamic Quanta Hierarchical Memory), a holographic associative memory architecture based on a 360-dimensional complex-valued hypervector space. By encoding key-value pairs as phase-shifted superpositions within a single C^360 vector, the system stores up to 10^9 entries in only 2,880 bytes of memory while maintaining constant-time O(1) retrieval at 27-28 µs regardless of dataset size. On an AMD Ryzen 7 5700X CPU (no GPU), empirical evaluation across seven orders of magnitude (10^3 to 10^9) demonstrates 100% retrieval accuracy under the proposed Phase-Resonance Similarity metric.

Fields of Study & Subjects

Algorithms and Data Compression Advanced Database Systems and Queries Network Packet Processing and Optimization

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 March 2026
Language
EN
Document type
Preprint